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RobMixReg
View on CRAN: Click
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Download and install RobMixReg package within the R console
Install from CRAN:
install.packages("RobMixReg")
Install from Github:
library("remotes")
install_github("cran/RobMixReg")
Install by package version:
library("remotes")
install_version("RobMixReg", "1.1.0")
Attach the package and use:
library("RobMixReg")
Maintained by
Wennan Chang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.RobMixReg . https://github.com/changwn/RobMixReg/issues . https://changwn.github.io/RobMixReg/ . RobMixReg results . RobMixReg.pdf . RobMixReg_1.1.0.tar.gz . RobMixReg_1.1.0.zip . RobMixReg_1.1.0.zip . RobMixReg_1.1.0.zip . RobMixReg_1.1.0.tgz . RobMixReg_1.1.0.tgz . RobMixReg_1.1.0.tgz . RobMixReg_1.1.0.tgz . RobMixReg_1.1.0.tgz . RobMixReg_1.1.0.tgz . RobMixReg archive . https://CRAN.R-project.org/package=RobMixReg .
First Published: 2020-03-25
Latest Update: 2020-08-05
Description:
Finite mixture models are a popular technique for modelling unobserved heterogeneity or to approximate general distribution functions in a semi-parametric way. They are used in a lot of different areas such as astronomy, biology, economics, marketing or medicine.
This package is the implementation of popular robust mixture regression methods based on different algorithms including: fleximix, finite mixture models and latent class regression; CTLERob, component-wise adaptive trimming likelihood estimation; mixbi, bi-square estimation; mixL, Laplacian distribution; mixt, t-distribution; TLE, trimmed likelihood estimation.
The implemented algorithms includes: CTLERob stands for Component-wise adaptive Trimming Likelihood Estimation based mixture regression; mixbi stands for mixture regression based on bi-square estimation; mixLstands for mixture regression based on Laplacian distribution; TLE stands for Trimmed Likelihood Estimation based mixture regression. For more detail of the algorithms, please refer to below references.
Reference: Chun Yu, Weixin Yao, Kun Chen (2017) .
NeyKov N, Filzmoser P, Dimova R et al. (2007) .
Bai X, Yao W. Boyer JE (2012) .
Wennan Chang, Xinyu Zhou, Yong Zang, Chi Zhang, Sha Cao (2020) .
How to cite:
Wennan Chang (2020). RobMixReg: Robust Mixture Regression. R package version 1.1.0, https://cran.r-project.org/web/packages/RobMixReg. Accessed 02 Apr. 2025.
Previous versions and publish date:
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Complete documentation for RobMixReg
Functions, R codes and Examples using
the RobMixReg R package
Some associated functions: CCLE_data . CSMR . CSMR_one . CSMR_predict . CSMR_train . CTLERob-methods . Compute_Rbase_SVD . DeOut . MLM . MLM_bic . MLM_cv . Rec_Lm . RobMixReg-class . TLE-methods . biscalew . bisquare . blockMap . colon_data . compPlot . denLp . flexmix_2 . gaussData . lars.lsa . logLik_mixtureReg . lsa . mixLp-methods . mixLp_one . mixlinrb_bi-methods . mixlinrb_bione . mixtureReg . orderedLines . plot_CTLE-methods . plot_mixtureReg . plot_mixtureRegList . rmr . simuData . simu_data_sparse . simu_func . simu_low .
Some associated R codes: CTLE.short.rob.R . RBSL.R . TLE.short.R . bi_square.short.R . compute_SVD.R . data.R . global_variable.R . lsa_function.R . mixL.short.R . mixtureReg.R . outer.R . outer2.R . plot_RobMixReg.R . plot_wrapper.R . simulation.R . vali_mode.R . Full RobMixReg package functions and examples
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